Moving object detection is a fundamental task for a variety of traffic applications.
In this paper the Daubechies and biorthogonal wavelet families are
exploited for extracting the relevant movement information in moving image
sequences in a 3D wavelet-based segmentation algorithm. The proposed algorithm
is applied for traffic monitoring systems. The objective and subjective
experimental results obtained by applying both wavelet types are compared
and interpreted in terms of the different wavelet properties and the characteristics
of the image sequences. The comparisons show the superior performance
of the symmetric biorthogonal wavelets in the presence of noisy images and
changing lighting conditions when compared to the application of high order
Daubechies wavelets. The algorithm is evaluated using simulated images in
the Matlab environment.